Chao Song
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Global and Planetary Change
- Mechanics of Materials
- Co-authors
- Yongyi YangP. Hendrik PretoriusMichael A. KingPan WuHaoyu JinXiaohong ChenMiles N. WernickBailin Yang
- Topics
- Medical Imaging Techniques and Applications (13 papers)Advanced MRI Techniques and Applications (12 papers)Cardiac Imaging and Diagnostics (8 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Graphics and Computer-Aided DesignComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Chao Song
41 papers receiving 326 citations
Peers
Comparison fields: 5 of 94
- Radiology, Nuclear Medicine and Imaging 115
- Biomedical Engineering 58
- Computer Vision and Pattern Recognition 48
- Global and Planetary Change 34
- Mechanics of Materials 26
Countries citing papers authored by Chao Song
This map shows the geographic impact of Chao Song's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chao Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Song more than expected).
Fields of papers citing papers by Chao Song
This network shows the impact of papers produced by Chao Song. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chao Song. The network helps show where Chao Song may publish in the future.
Co-authorship network of co-authors of Chao Song
This figure shows the co-authorship network connecting the top 25 collaborators of Chao Song. A scholar is included among the top collaborators of Chao Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chao Song. Chao Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 9 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 9 | |
| 12 | 23 | |
| 13 | 8 | |
| 14 | 29 | |
| 15 | 8 | |
| 16 | 5 | |
| 17 | 6 | |
| 18 | 7 | |
| 19 | 9 | |
| 20 | 2 |
About Chao Song
Chao Song is a scholar working on Computer Graphics and Computer-Aided Design, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 51 papers that have together received 328 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (13 papers), Advanced MRI Techniques and Applications (12 papers) and Cardiac Imaging and Diagnostics (8 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (115 citations), Computer Graphics and Computer-Aided Design (15 citations) and Computer Vision and Pattern Recognition (48 citations). Chao Song has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yongyi Yang, P. Hendrik Pretorius, Michael A. King, Pan Wu, Haoyu Jin, Xiaohong Chen, Miles N. Wernick, Bailin Yang, Jun Shen and Dongdong Wang. Their work appears in journals such as Chemical Physics Letters, IEEE Transactions on Medical Imaging and Pattern Recognition.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.